Hey, I'm Robiul.
I'm a Machine Learning Engineer
I specialize in designing and deploying scalable ML systems across fintech, logistics, and the public sector. From architecting neural networks to optimizing MLOps pipelines, I turn complex data into production-ready intelligence. Outside of training models, I enjoy UI design, building side projects, and supporting FC Barcelona.
About.
I am a Machine Learning Engineer with a passion for turning raw data into actionable intelligence. With a solid foundation in Computer Science and full-stack development, I focus on building end-to-end ML solutions that are both technically rigorous and user-centric.
My journey started with a Computer Science degree from East Delta University, where I developed a fascination for how algorithms can solve real-world problems. I’ve spent my time mastering the intersection of software engineering and data science, ensuring that the models I build aren't just accurate, but also scalable and deployable.
I have a strong interest in MLOps—the art of streamlining the machine learning lifecycle. I enjoy working on the entire pipeline: from data preprocessing and feature engineering to model training and setting up automated deployment environments.
My core technical stack includes Python (Scikit-Learn, TensorFlow/PyTorch), TypeScript, and SQL. I am currently looking for my first professional role where I can contribute to high-impact ML projects and grow alongside a team of experienced engineers.
If you’re looking for a dedicated engineer who is ready to tackle complex data challenges and build the next generation of AI-driven products, let’s connect. 🔗
Currently Exploring
Tech Stack
Design & Multimedia
Projects.
Experience.
Led the machine learning strategy for the CosmoMind project. I focused on architecting predictive models using satellite data and implementing computer vision algorithms to identify celestial patterns. I was responsible for data preprocessing, model selection, and ensuring the scalability of the AI solution under competition constraints.
Served as the primary ML Engineer, designing and deploying intelligence-driven features. I built end-to-end pipelines for data collection, cleaning, and model inference. I worked closely with the backend team to integrate these models into a production-ready API, focusing on reducing latency for real-time predictions.